This study reconciles existing literature on stock market efficiency and mutual fund performance by developing a framework to test whether fund managers are able to exploit market inefficiencies. We find a positive relationship between alpha and weak-form market efficiency. Most funds are unable to outperform the market systematically, although a few are able to exploit relatively inefficient markets. Top performing funds are characterised by a better management of downside risk in times of market distress, whilst simultaneously exploiting learning effects when markets return to equilibrium. By conditioning fund performance on the state of the underlying market, we propose a conditional alpha ratio, which helps to better understand fund performance and can improve the fund selection process for investors.

This paper examines the association between corporate social responsibility (CSR), product market competition (PMC) and shareholder wealth by analysing CSR and market data from January 2006 to December 2012 (excluding 2009) in Korea. We focus on the role of PMC, which has been ignored in previous studies of CSR. Our empirical analyses indicate that PMC plays a significant role in explaining the relationship between a firm's CSR activity and its stock returns. More specifically, we find that CSR activities significantly increase stock returns when PMC is low. This result implies that when competition is low, the effect of CSR is consistent with the stakeholder value maximisation theory.

This study examines arbitrage costs and the persistence of the size, value and momentum premiums on the Johannesburg Stock Exchange (JSE). Two arbitrage costs are considered: transaction and holding costs. Transaction costs refer to indirect and direct costs of engaging in arbitrage. Holding costs relate to the level of idiosyncratic risk that arbitrageurs expose themselves to in pursuit of an individual strategy. We examine monthly price and accounting data of all JSE listed shares over the period 1 January 1992 to 30 November 2014. The effects of idiosyncratic risk are evaluated with asymmetric and GARCH-in-mean models using zero-cost portfolio return series. The results reveal significant and persistent value and momentum effects. The value premium is highly sensitive and negatively related to direct transaction costs. Conversely, momentum has greater sensitivity to indirect transaction costs and displays a negative relationship. An increase in idiosyncratic risk results in an increase in the value premium. However, the momentum premium does not react positively to an increase in idiosyncratic risk. The findings imply that the costs of arbitrage play a large role in the persistence and existence of the value premium, yet the same cannot be said for medium-term momentum in share prices.

Portfolio construction plays a critical role in adding performance to a fund. Central to portfolio construction are the two primary inputs: the vector of forecast returns and the covariance matrix. Our focus is on the covariance matrix. With guidance from the literature we consider the suitability of two simple estimators, four shrinkage estimators and three blended estimators for mean-variance portfolio construction in the South African environment. Our assessment frameworks comprise a risk-centric framework based on minimum variance portfolios (MVPs) as well as a return-centric framework. Our findings based on a South African equity setting reveal that there are notable differences between the compositions of the MVPs of the covariance estimators. Furthermore, we find that alternative covariance estimators do yield better out-of-period performance in terms of lower realised risks than the sample covariance matrix. In our return-based assessment framework, we considered scenarios of perfect skill and less-than-perfect skill at forecasting returns. In the former case, we found that all of the estimators produced optimal portfolios that substantially outperformed the optimal portfolio derived from the sample covariance matrix. Considering the MVP framework, as well as the return-based framework, we conclude that all of the estimators considered performed better than the sample covariance matrix, effectively reducing the sampling error in the sample covariance without introducing too much specification error. However, no one estimator could be singled out as consistently superior in the South African setting over a range of test metrics considered.